The present invention relates to a method of deriving a quantitative measure of a degree of calcification of a blood vessel, e.g. an aorta.
Inpainting is a technique that originates from retouching paintings where one wants to recreate lost or damaged structures in a legible way. Digital inpainting uses spatial or frequency information to restore partially damaged/removed images.
Various inpainting techniques are known that enable image restoration, in particular for photographs, videos and films.
It is known to detect and inpaint small regions in mammograms that possibly define a micro calcification to enable detection of calcified regions. Subsequently, features such as the average and the standard deviation of intensity values are extracted from both the pre- and the post-inpainting regions. A classifier is trained to distinguish between true micro calcifications and false positives based on the extracted features. The comparison between a region and its inpainting is used to enable detection. Thus a binary decision of whether a region is abnormal, i.e. different from its surroundings, is made.
There are, however, no methods available at present that use inpainting to give more than a basic indication of the presence of a calcification. In the present invention, it has been realised that such a method may be useful in the diagnosis of various diseases, for example, atherosclerosis.
Atherosclerosis is a process in which deposits of fatty substances, cholesterol, cellular waste products, calcium and other products build up in the inner lining of an artery.
Calcifications in the abdominal aorta, or at other sites such as the coronary arteries, are an important predictor for assessing cardiovascular morbidity and mortality.
Previous known methods of providing a reproducible measurement of the amount of calcified deposits in the aorta include several automatic and semi-automatic calcium scoring methods for use with computed tomography (CT) scans. CT scans are useful when used to identify and quantify atherosclerosis. However, the expense involved in CT scans prevents this method from being used in more routine diagnoses.
A previous known approach involves manually quantifying the severity of aortic calcifications in radio-graphs by providing an antero-posterior severity score. For this score, as shown in FIG. 2, the lumbar part of the aorta is divided in four segments adjacent to the four vertebra L1-L4, and the severity of the anterior and posterior aortic calcification are graded individually for each segment on a 0-3 scale. The results are summed in a composite severity score ranging from 0 to 24. A manual scoring system as described has been successfully applied in epidemiological studies but this method does not allow for describing subtle changes in disease progression and the method is both labour-intensive and prone to inter- and intra-observer variations.
The inventors of the present invention have recognised that it would be desirable to provide an automated calcification detection scheme that allows for automatic scoring according to current semi-quantitative standards as well as for continuous and more precise quantification.